Synthesis and final recommendations on the development of a European Information System for Organic Markets. = Deliverable D6 of the European Project EISfOM QLK5-2002-02400

Executive summary European markets for organic products are growing rapidly, but the market information available in most European countries is woefully inadequate. Often only very basic data such as certified organic holdings and land area are reported, and sometimes not even individual crop areas or livestock numbers. Important market data, such as the amount of production, consumption, international trade or producer and consumer prices, do not exist in most European countries. In some European countries there are only rough estimates of the levels of production and consumption. There is no standardisation and data are seldom comparable. Furthermore, detailed information on specific commodities is missing. Hence, investment decisions are taken under conditions of great uncertainty. Policy evaluation, including periodic monitoring of the European Action Plan for Organic Food and Farming and RDP 2007-2013, will require many other data in addition to those regarding production structures and financial data that are already available, but obtaining this information would require a new EU-wide data collection and processing system (DCPS) to be put in place. The European Information System for Organic Markets (EISfOM) project is an EUfunded Concerted Action which has analysed and documented the current situation and proposed ways in which organic data collection and processing systems (DCPS) can be improved by means of: • improvement in the current situation of data collecting and processing systems for the organic sector • innovation in data collection and processing systems for the organic sector • integration of conventional and organic data collection and processing systems This report summarises the most relevant findings of the EISfOM project, which are analysed in the main project reports: Wolfert, S., Kramer, K. J., Richter, T., Hempfling, G., Lux. S. and Recke, G. (eds.) (2004). Review of data collection and processing systems for organic and conventional markets. EISfOM (QLK5-2002-02400) project deliverable submitted to European Commission. www.eisfom.org/publications. Recke, G., Hamm, U., Lampkin, N., Zanoli, R., Vitulano, S. and Olmos, S. (eds.) (2004a) Report on proposals for the development, harmonisation and quality assurance of organic data collection and processing systems (DCPS). EISfOM (QLK5-2002-02400) project deliverable submitted to European Commission. www.eisfom.org/publications. Recke, G., Willer, H., Lampkin, N. and Vaughan, A. (eds.) (2004b). Development of a European Information System for Organic Markets – Improving the Scope and Quality of Statistical Data. Proceedings of the 1st EISfOM European Seminar, Berlin, Germany, 26-27 April, 2004. Research Institute of Organic Agriculture (FiBL), Frick, Switzerland. www.eisfom.org/publications. Gleirscher, N., Schermer, M., Wroblewska, M. and Zakowska-Biemans, S. (2005) Report on the evaluation of the pilot case studies. EISfOM (QLK5-2002-02400) project deliverable submitted to European Commission. www.eisfom.org/publications. QLK5-2002-02400 European Information System for Organic Markets (EISfOM) D6 final report Rippin, M. and Lampkin, N. (eds.) (2005) Framework for a European Information System for Organic Markets. Unpublished report of the project European Information System for Organic Markets (EISfOM) (QLK5-2002-02400). Rippin, M., Willer, H., Lampkin, N., and Vaughan A. (2006). Towards a European Framework for Organic Market information, Proceedings of the 2nd EISfOM European Seminar, Brussels, November 10 and 11, 2005. Research Institute of Organic Agriculture (FiBL), Frick, Switzerland. www.eisfom.org/publications

Report on proposals for the development, harmonisation and quality assurance of organic data collection and processing systems (DCPS)

This report represents the conclusion of the European seminar on development, harmonisation and quality assurance of organic data collection and processing systems (Berlin, April 2004) as well as of the first phase of the EISFOM-project. - In the first chapter the objectives and general approach of this workpackage are described. - Chapter 2 focuses on quality assurance, the main results of WP2 and WP3 and the European Seminar in Berlin (see Recke et al. 2004; https://orgprints.org/2935/. Furthermore, the strengths and weaknesses of organic DCPS (data collection and processing systems) are analysed and the chapter closes with proposals for the development of organic DCPSs. - Chapter 3 focuses on results of expert interviews on the main barriers for the implementation of improved organic statistical data collection and processing systems. - Chapter 4 gives a summary and some general conclusions are drawn. This report provides perspectives on how the above mentioned issues of the European Action Plan might be implemented

Recommender Systems

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports

A Hybrid Web Recommendation System based on the Improved Association Rule Mining Algorithm

As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system. In case of collaborative recommen-dation systems, these try to seek out users who share same tastes that of given user as well as recommends the websites according to the liking given user. Whereas the content based recommendation systems tries to recommend web sites similar to those web sites the user has liked. In the recent research we found that the efficient technique based on asso-ciation rule mining algorithm is proposed in order to solve the problem of web page recommendation. Major problem of the same is that the web pages are given equal importance. Here the importance of pages changes according to the fre-quency of visiting the web page as well as amount of time user spends on that page. Also recommendation of newly added web pages or the pages those are not yet visited by users are not included in the recommendation set. To over-come this problem, we have used the web usage log in the adaptive association rule based web mining where the asso-ciation rules were applied to personalization. This algorithm was purely based on the Apriori data mining algorithm in order to generate the association rules. However this method also suffers from some unavoidable drawbacks. In this paper we are presenting and investigating the new approach based on weighted Association Rule Mining Algorithm and text mining. This is improved algorithm which adds semantic knowledge to the results, has more efficiency and hence gives better quality and performances as compared to existing approaches.Comment: 9 pages, 7 figures, 2 table

Indonesia Sustainable Fisheries Value Chain Assessments

Wilderness Markets, with the support of the David and Lucile Packard Foundation and the Gordon and Betty Moore Foundation, undertook a series of fishery value chain assessments to better understand the opportunities and constraints for private impact capital to flow into wild-capture fisheries markets in Indonesia. Building on extensive impact-focused investment experience in agricultural value chains, the objectives were to:*  Identify and categorize potential impact investment opportunities in wild-capture fisheries utilizing a combination of impact investment frameworks.*  In the absence of impact investment opportunities, document value chain constraints preventing such opportunities.*  Support the creation of sustainable wild-capture fisheries investment strategies by identifying appropriate frameworks for the assessment and development of intervention opportunities.Wilderness Markets assessed four developing country fisheries (DCFs) in two countries, with a particular focus on Indonesia, plus one fishery in California, US, for comparison. This document focuses on Indonesia and summarises our assessment of the blue swimming crab, snapper, yellowfin and skipjack tuna seafood value chains. Each fishery assessed provided a piece of a larger puzzle, allowing Wilderness Markets to identify the components of a sustainable seafood value chain and its relationship to stock health which, in turn, drives value chain health.This document provides a summary of the findings in Indonesia

Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis

Product recommendation and preference tracking systems have been adopted extensively in e-commerce businesses. However, the heterogeneity of product attributes results in undesired impediment for an efficient yet personalized e-commerce product brokering. Amid the assortment of product attributes, there are some intrinsic generic attributes having significant relation to a customer’s generic preference. This paper proposes a novel approach in the detection of generic product attributes through feature analysis. The objective is to provide an insight to the understanding of customers’ generic preference. Furthermore, a genetic algorithm is used to find the suitable feature weight set, hence reducing the rate of misclassification. A prototype has been implemented and the experimental results are promising

Connecting the Dots: Linking Sustainable Wild Capture Fisheries Initiatives and Impact Investors

Wilderness Markets undertook a series of fishery value chain assessments to better understand the opportunities and constraints for private impact capital to flow into wild capture fisheries markets. Given the investments in developing sustainable fisheries pilots, Wilderness Markets expected to identify a range of investment opportunities in each of the fisheries assessed. However, they did not find investment opportunities that could address the suite of challenges associated with improving financial and social outcomes, while also contributing to conservation outcomes, particularly in developing country fisheries. Wilderness Markets' research indicates the lack of triple-bottom line (TBL) investment opportunities is due to six main constraints to an economically sustainable fisheries value chain—data, management, market differentiation, infrastructure, finance and the lack of investable entities